code: def test_scores_are_equivalent():
      _assert_test_scores_equivalent(
          "h2o_only_pipeline_with_h2o_frame",
          "h2o_only_pipeline_with_numpy_arrays",
      )
      _assert_test_scores_equivalent(
          "mixed_pipeline_with_numpy_arrays",
          "generic_estimator_with_distribution_param",
      )
  
file_path: h2o-3/h2o-py/tests/testdir_sklearn/pyunit_sklearn_regression_pipeline.py
imports: import importlib, inspect, os, sys
  import numpy
  from sklearn.datasets import make_regression
  from sklearn.decomposition import PCA
  from sklearn.metrics import r2_score
  from sklearn.model_selection import train_test_split
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import StandardScaler
  import h2o
  from h2o.sklearn import H2OGradientBoostingEstimator, H2OGradientBoostingRegressor, H2OScaler, H2OPCA
  from h2o.sklearn.wrapper import H2OConnectionMonitorMixin
  from tests import pyunit_utils, Namespace
label_desc: Use image node_id 7 for calling a global function with example usage: test_scores_are_equivalent() without return types